{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import gym\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2016-09-12 09:17:55,691] Making new env: MountainCar-v0\n"
     ]
    }
   ],
   "source": [
    "env = gym.envs.make(\"MountainCar-v0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEACAYAAABfxaZOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117e09860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEACAYAAABfxaZOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEkf+P4V/x10kXmYCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117d64a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env.reset()\n",
    "plt.figure()\n",
    "plt.imshow(env.render(mode='rgb_array'))\n",
    "\n",
    "[env.step(0) for x in range(10000)]\n",
    "plt.figure()\n",
    "plt.imshow(env.render(mode='rgb_array'))\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
